Real-Time Data Processing with Sliding Window Correction
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Solution Overview
Problem
Enterprise servers face challenges in processing large volumes of data in real-time due to stringent timing requirements, leading to inaccuracies and potential data loss, which affects the quality of data records.
Innovation Solution
A system that processes incoming data in real-time initially, followed by non-real-time processes to correct inaccuracies, using a sliding window data structure with multiple slots for timestamped event data, allowing for more accurate data generation and correction over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If real-time processing is performed under tight time constraints, then processing speed is improved, but data accuracy deteriorates
Solution Approach 1:
The processing system is divided into two independent segments: a real-time processing component that operates under tight time constraints to meet latency requirements, and a non-real-time processing component that operates with relaxed time constraints to ensure data accuracy. Each segment handles the same event data but with different processing priorities, allowing the system to satisfy both speed and accuracy requirements simultaneously.
2Speed
If real-time processing is performed under tight time constraints, then processing speed is improved, but data reliability deteriorates
Solution Approach 1:
The system implements a feedback mechanism where the non-real-time processing results are used to correct and verify the real-time processing outputs. The non-real-time process acts as a feedback loop that identifies and corrects inaccuracies introduced during rapid real-time processing, thereby improving overall data reliability without compromising real-time response performance.
3Measurement precision
If non-real-time processes are performed to correct inaccuracies, then data accuracy is improved, but processing time increases
Solution Approach 1:
The real-time processing performs preliminary action by quickly generating initial data records under tight time constraints to meet immediate latency requirements. The non-real-time processing then performs corrective action on these preliminary results, allowing the system to deliver timely preliminary responses while subsequently improving accuracy without adding significant delay to the primary real-time response.
Data Source
AI summary
Methods and systems for processing incoming data in real-time are described herein. The incoming data is processed in real-time to generate data records that may be improved over time, for example, by automatically correcting inaccurate data in the records. In some embodiments, when data is received, a real-time process is initially performed on the received data under a first time constraint to produce first data for a data record. Subsequently, one or more non-real-time processes are then performed on the received data under a second time constraint to produce second data for the data record. The second data may be used to update the data record, for example, to correct any inaccuracy caused by the real-time process of the received data. Preferably, the second time constraint is longer than the first time constraint.